Prevalence of chronic conditions and influenza vaccination coverage rates in Germany: Results of a health insurance claims data analysis

Abstract Background The significant annual burden caused by seasonal influenza has led to global calls for increased influenza vaccination coverage rates (VCRs). We aimed to estimate the proportion of the German population at high risk of serious illness from influenza due to chronic conditions and to estimate age‐specific VCRs of people with/without chronic conditions. Methods Using health insurance claims data covering nine influenza seasons (2010–2019), we assessed up to 7 million insured individuals per season across all German regions. Individuals were classified according to age and presence of chronic health conditions. VCRs were estimated using outpatient healthcare utilization documentation. Results In the 2018–2019 influenza season, 47.3% of individuals had ≥1 chronic condition. Most common were circulatory disorders, accounting for more than a third of individuals with ≥1 condition. Prevalence of chronic diseases, and therefore the proportion of high‐risk individuals, increased slightly over time across most age groups. A downward trend in influenza VCRs was observed in all age groups until the 2017–2018 season, followed by a noticeable increase in the 2018–2019 season. Highest VCRs occurred among individuals of ≥60 years, with a 38.5% VCR for this age group in the 2018–2019 season. Several factors, including age, chronic condition type, and geographical location, affected VCRs. Conclusions Influenza VCRs in individuals at high risk of severe complications from influenza infection are insufficient. Our results suggest that intensified public health efforts are necessary to reach the World Health Organization vaccination coverage target of 75%.


| INTRODUCTION
Each year, influenza epidemics cause considerable morbidity and mortality worldwide. In the 2017-2018 season, the number of deaths attributable to influenza in Europe was estimated to be 152,000. 1 A study on communicable diseases in Europe revealed that influenza accounts for 30% of the total burden of 31 selected infectious diseases in terms of disability-adjusted life years (DALYs). 2 Globally, influenza has also been shown to have a significant economic burden, with both direct and indirect costs. For example, a recent study covering data from 2015 in the United States, across all age groups, estimated that direct medical costs amounted to approximately $3.2 billion nationally. 3 The same study showed that influenza has a substantial impact on workplace activity, with 20 million days of productivity lost in the United States during 2015. 3 In 2003, the World Health Organization (WHO) stated that member states should aim to achieve an influenza vaccination coverage rate (VCR) of 75% or higher among older people (defined as those aged ≥65 years in 76% of the responding countries but refers to those aged ≥60 years in Germany) and individuals with chronic illnesses and that this target should be achieved by 2010. 4 This motion was reaffirmed by the European Parliament and extended in a 2009 European Council recommendation, whereby European countries should reach 75% vaccination coverage in older age groups by 2015. 5 In Germany, the current influenza immunization recommendation issued by the Standing Committee on Vaccination (STIKO) focuses on individuals aged ≥60 years, individuals with underlying chronic conditions, pregnant women, and healthcare workers. 6 It is especially important to vaccinate those with chronic conditions because vaccination has been associated with improved clinical outcomes among this population, particularly individuals with chronic respiratory disease and cardiovascular disease. 7,8 Currently, available information on influenza VCRs for Germany is limited since published evidence does not always include a detailed breakdown by age and/or risk status.
Furthermore, large parts of the official VCR surveillance by the Robert Koch Institute (RKI) are only reported graphically. In this study, we first aimed to estimate the proportion of the German population that is at high risk of developing severe influenza complications due to underlying chronic conditions. Second, we aimed to estimate agespecific influenza VCRs in the overall population and in individuals with and without chronic conditions.

| Data source and study period
Our study is based on claims data of a large German Statutory Health Insurance (SHI) fund (BARMER) covering nine consecutive influenza seasons (2010-2011 to 2018-2019). Of the 8.8 million individuals covered by this fund, up to 7 million insured individuals were included in the analysis depending on the season, corresponding to between 6.6% and 8.7% of the national population (supporting information Table S1). Data were included across all regions of Germany. The health insurance claims data contained information on outpatient and inpatient diagnoses and corresponding healthcare resource use.
An influenza season was defined to reach from the beginning of the third quarter of an index year to the end of the second quarter of the following year. This expanded definition of a season was chosen to capture all influenza vaccine administrations throughout a year.
The study period of every influenza season comprises eight quarters, divided into an analysis period of four quarters, preceded by a pre-observation period of four quarters. For example, the study period for the 2017-2018 season starts in the third quarter of 2016 and ends in the second quarter of 2018 (supporting information Figure S1). The analysis period was used to estimate the VCRs, and the pre-observation period was used to identify individuals with chronic conditions. For every influenza season, we included all insured individuals who had continuous insurance coverage in the previous season (pre-observation period) and also had continuous insurance coverage, or died, during the season of interest (analysis period).
As the study did not gather primary patient-or individual-level data or involve any interventions, formal ethical approval was not sought.

| Identification of individuals with chronic conditions
For every season, insured individuals with chronic conditions were identified using the International Classification of Diseases (ICD) 10 diagnoses (see Table 1). ICD-10 code selection was based on previous studies that estimated the size of the population at risk because of chronic conditions 9,10 ; codes were added or excluded to reflect the relevant spectrum of chronic conditions. Individuals were considered chronically ill if they fulfilled ≥1 of the following criteria in the pre-observation period: a primary inpatient diagnosis, two same confirmed outpatient diagnoses in two different quarters, two same secondary inpatient diagnoses in two different quarters, or a confirmed outpatient diagnosis and the same secondary inpatient diagnosis in two different quarters. Outpatient diagnoses that were only documented as suspected diagnoses by the respective physician were excluded.

| Proportion of population with chronic health conditions
In the 2018-2019 season (the most recent with data available for our study), 47.3% of the studied population had at least one chronic condition, and age-specific prevalence ranged from 8.8% in the youngest age group (1-9 years) to 92.4% in the oldest age group (≥80 years) ( Figure 1). A similar increase with age was observed in previous seasons (Table 2). Within most age groups, the prevalence of chronic diseases also increased over time. Table 3 shows the age-specific prevalence of all chronic disease groups studied for the 2018-2019 season. In this season, the prevalence of chronic circulatory diseases was 36.9% in the overall population, followed by chronic respiratory diseases (11.1%), diseases associated with a weakened immune system (10.7%), and diabetes (10.6%). Beginning with the age group of 30-39 years, circulatory diseases were the leading group of chronic diseases, mainly due to hypertension. In the age groups ≤30 years, chronic respiratory diseases were the group with the highest prevalence.   (Table 4). Table 4 provides an overview of age-specific VCRs in all the studied seasons. Influenza vaccine uptake varied widely with age. The highest VCRs were consistently found in people aged ≥60 years. Within this age group, rates were higher among those aged 70-79 years compared with those aged 60-69, while rates among those aged ≥80 were marginally higher than those aged 70-79. VCRs among females were slightly higher than among males in most age groups across all seasons.

| VCRs
Coverage rates also varied between individuals with and without chronic conditions. In all age groups, influenza VCRs in individuals with underlying chronic conditions were higher than in those who were not chronically ill. In the 2018-2019 season, age-specific coverage in individuals with chronic conditions ranged from 7.6% to 49.5%, and coverage in the healthy population ranged from 2.7% to 24.3% ( Figure 4). In 2018-2019, the highest VCR of 49.5% was seen in individuals aged ≥80 years with chronic conditions. The rate in individuals aged ≥60 years with chronic conditions (a group that could be considered doubly at risk) was only 43.3%.  Circulatory  I05-I09, I10-I15, I20-I25, I26-I28,  I30-I52, I60-I69, G45, Q20-Q24, Heart failure I50 Ischemic heart diseases I20-I25 Pulmonary heart diseases I26-I28 Disorders involving the immune mechanism D80-D90 Abbreviations: AIDS, acquired immunodeficiency syndrome; COPD, chronic obstructive pulmonary disease; HIV, human immunodeficiency virus; ICD, International Classification of Diseases.
VCRs also varied with the type of chronic disease (Table 5). For example, vaccine uptake was lower in individuals with asthma than in those with ischemic heart disease, heart failure, or diabetes when looking at the coverage rates in the total group. Influenza VCRs varied widely by region (

| DISCUSSION
Our analysis of the BARMER statutory health insurance database in Germany showed that the prevalence of chronic diseases has increased slightly over time, but VCRs have remained consistently  Approximately 80% of the population aged ≥60 years had at least one chronic condition, as did nearly 50% of the population aged 50-59. The morbidity profile was dominated by circulatory diseases, particularly among the older age groups. The proportion of the population with more than one chronic condition also increased with age.
Individuals within this category accounted for an increased proportion of morbidity among older age groups, particularly those aged ≥60 years.
The prevalence data presented in our study for specific chronic diseases (based on both inpatient and outpatient diagnoses) are similar to those reported in other studies, which all used outpatient claims data of the complete German SHI population. In our study, diabetes prevalence was 10.6% overall with a marked increase between the 40-to 49-and 50-to 59-year age groups and then between each subsequent age decade. This is in line with results reported in another German claims data analysis, where the prevalence of diabetes was 9.8% in 2015. 11 The prevalence of asthma observed in our study was 6.6%, compared with 5.7% in another claims data analysis in 2016. 12 19 Coverage was slightly higher among females than males, and notably higher among older age groups, as noted in our study. Although many of that study's findings are similar to ours, there were key differences in the methods used. 19 Firstly, There is a noticeable trend in the timing of vaccinations, with the majority taking place in October, followed by a sharp decline after November. This is in line with expectations that the population is encouraged to be vaccinated before the start of the influenza season.
The STIKO recommends that annual influenza vaccination should take place in autumn. 6 Regional differences included lower VCRs in the south of      attitudes towards vaccination against influenza and regional VCRs are correlated. 22 The study also showed that the attitude patterns of GPs' patients and colleagues appear to influence the GPs and should therefore be included in future interventions to increase influenza vaccine uptake at a regional level. 22 Bӧdeker et al. found that the most common reasons for low influenza VCR in Germany are a general mistrust of vaccination along with the perception that influenza is not a dangerous disease, both of which were stated by more than 20% of interviewees. 23  One element that has been repeatedly mentioned as a relevant factor is patient reminder interventions. 26,27 A systematic review found that patient reminder and recall systems can effectively improve VCRs. 28 Digital immunization management systems can help integrate patient reminders and invitations into the daily workflow of primary care practices. 29 The current study possesses several strengths that reinforce the importance of our results. Firstly, this is one of the first publications for Germany with data on both size of the population at risk and asso- was not possible to evaluate data from Berlin separately, these data were included in their entirety in the overall analysis.
In addition, the definition of risk groups presents a challenge; other studies do not always transparently document the ICD-10 codes used. Therefore, we are unable to confirm if the same codes were used across studies, which may reduce the strength of our comparisons with other analyses. Some codes may also have been entered into the database incorrectly. For example, in Table 4, the prevalence of COPD in children aged 1-9 is shown as 1.14%. Some physicians may have used this code when no specific cause for respiratory disease could be identified, or they may have used "COPD" as an umbrella term for lung diseases of a chronic obstructive nature. Nonetheless, the data that we present here provide valuable insight into influenza VCRs among the at-risk population and how they have changed over time.

ETHICS STATEMENT AND INFORMED CONSENT
As the study did not gather patient or individual-level data or involve any interventions, formal ethical approval was not sought, and informed consent was not applicable.

PEER REVIEW
The peer review history for this article is available at https://publons. com/publon/10.1111/irv.13054.

DATA AVAILABILITY STATEMENT
The data are not publicly available due to data protection regulations of the data holder and national legislation.